uses af Determine the estimated regression equation 4 =B₁ + B₁ X the least squares method. b. Based on the results of A), determine the estimated value of the Weight ŵ 1 for all observations. (1-7) c. Based on the results B/. determine the estimated regression equation /w =B₁ + B x using the weighted least squares method.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Question

pleasee help mee

No
X
Y
1
24
0
2
24
1
3
25
1
4
25
1
5
30
0
6
31
0
7
27
1
8
9
31 26
0
1
10
25
1
11
30
0
12
31
0
Transcribed Image Text:No X Y 1 24 0 2 24 1 3 25 1 4 25 1 5 30 0 6 31 0 7 27 1 8 9 31 26 0 1 10 25 1 11 30 0 12 31 0
A study was conducted to determine the effect of body mass index (x)
on a person's likelihood of suffering from heart disease (y) with
a
Vanable
Y
-
af
{
1
0,
t
if you don't have heart disease
have heart disease.
if
you
If the relationship is expressed in a linier model X = P₁ + @²₁₂₁₂ x + ε
then based on the data in the following table:
Determine the estimated regression equation 4 =B₁ + B₁₂ X uses
the least
squares
method.
b.) Based on the results of A), determine the estimated value of the
Weight
ŵ
=
1
for all observations.
(1-9)
Based on the results B/ determine the estimated
equation 7w = 30 +3₁ x using the weighted least
method.
regression
squares
Transcribed Image Text:A study was conducted to determine the effect of body mass index (x) on a person's likelihood of suffering from heart disease (y) with a Vanable Y - af { 1 0, t if you don't have heart disease have heart disease. if you If the relationship is expressed in a linier model X = P₁ + @²₁₂₁₂ x + ε then based on the data in the following table: Determine the estimated regression equation 4 =B₁ + B₁₂ X uses the least squares method. b.) Based on the results of A), determine the estimated value of the Weight ŵ = 1 for all observations. (1-9) Based on the results B/ determine the estimated equation 7w = 30 +3₁ x using the weighted least method. regression squares
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